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DBMS > Google Cloud Spanner vs. Hazelcast vs. Milvus vs. Trafodion

System Properties Comparison Google Cloud Spanner vs. Hazelcast vs. Milvus vs. Trafodion

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Editorial information provided by DB-Engines
NameGoogle Cloud Spanner  Xexclude from comparisonHazelcast  Xexclude from comparisonMilvus  Xexclude from comparisonTrafodion  Xexclude from comparison
DescriptionA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A widely adopted in-memory data gridA DBMS designed for efficient storage of vector data and vector similarity searchesTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSKey-value storeSearch engineRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.11
Rank#89  Overall
#46  Relational DBMS
Score10.70
Rank#47  Overall
#5  Key-value stores
Score0.37
Rank#264  Overall
#18  Search engines
Score0.46
Rank#246  Overall
#118  Relational DBMS
Websitecloud.google.com/­spannerhazelcast.commilvus.iotrafodion.apache.org
Technical documentationcloud.google.com/­spanner/­docshazelcast.org/­imdg/­docsmilvus.io/­docs/­overview.mdtrafodion.apache.org
DeveloperGoogleHazelcastApache Software Foundation, originally developed by HP
Initial release2017200820192014
Current release5.1, March 20222.0, January 20222.3.0, February 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, GoC++, Java
Server operating systemshostedAll OS with a Java VMLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Linux
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesNumeric and Stringyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes infothe object must implement a serialization strategynono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes infoQuery statements complying to ANSI 2011SQL-like query languagenoyes
APIs and other access methodsgRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesnoJava Stored Procedures
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.yes infoReplicated Mapyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoStrict serializable isolationone or two-phase-commit; repeatable reads; read commitednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlnofine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud SpannerHazelcastMilvusTrafodion
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosVideo media : video understanding, video deduplication. E-commerce and mobile applications...
» more
Key customersMilvus is trusted by over 1,000 enterprises, including Baidu, eBay, IKEA, LINE, Shopee,...
» more
Market metricsAs of March 2022, 9.8k+ GitHub stars 1.4k+ Github forks 871k+ docker pulls 2k+ community...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Managed...
» more

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More resources
Google Cloud SpannerHazelcastMilvusTrafodion
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